Low-Rank and Sparse Modeling for Visual Analysis, Yun Fu
Автор: Yun Fu Название: Low-Rank and Sparse Modeling for Visual Analysis ISBN: 3319119990 ISBN-13(EAN): 9783319119991 Издательство: Springer Рейтинг: Цена: 15372.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book provides a view of low-rank and sparse computing, especially approximation, recovery, representation, scaling, coding, embedding and learning among unconstrained visual data.
Описание: This unique text/reference presents a comprehensive review of the state of the art in sparse representations, modeling and learning. covers feature representation and learning, sparsity induced similarity, and sparse representation and learning-based classifiers;
Автор: Michael Elad Название: Sparse and Redundant Representations ISBN: 1489982450 ISBN-13(EAN): 9781489982452 Издательство: Springer Рейтинг: Цена: 9083.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book introduces sparse and redundant representations with a focus on applications in signal and image processing. It details mathematical modeling for signal sources along with how to use the model for tasks such as denoising, restoration and separation.
Описание: This book treats the topic of extending the adaptive filtering theory in the context of massive multichannel systems by taking into account a priori knowledge of the underlying system or signal.
Автор: Oreifej, Omar Shah, Mubarak Название: Robust subspace estimation using low-rank optimization ISBN: 3319041835 ISBN-13(EAN): 9783319041834 Издательство: Springer Рейтинг: Цена: 13275.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Robust Subspace Estimation Using Low-Rank Optimization
Автор: Stan Z. Li Название: Markov Random Field Modeling in Image Analysis ISBN: 1848002785 ISBN-13(EAN): 9781848002784 Издательство: Springer Рейтинг: Цена: 19564.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Markov random field (MRF) theory provides a basis for modeling contextual constraints in visual processing and interpretation. Various vision models are presented in a unified framework, including image restoration and reconstruction, edge and region segmentation, texture, stereo and motion, object matching and recognition, and pose estimation.
Описание: This unique text/reference presents a comprehensive review of the state of the art in sparse representations, modeling and learning. covers feature representation and learning, sparsity induced similarity, and sparse representation and learning-based classifiers;
Автор: Avishy Y. Carmi; Lyudmila Mihaylova; Simon J. Gods Название: Compressed Sensing & Sparse Filtering ISBN: 3642383971 ISBN-13(EAN): 9783642383977 Издательство: Springer Рейтинг: Цена: 27950.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book presents fundamental concepts, methods and algorithms able to cope with undersampled data. It introduces the concept of compressive sampling, which is also called compressed sensing.
Автор: Avishy Y. Carmi; Lyudmila Mihaylova; Simon J. Gods Название: Compressed Sensing & Sparse Filtering ISBN: 366250894X ISBN-13(EAN): 9783662508947 Издательство: Springer Рейтинг: Цена: 20896.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book presents fundamental concepts, methods and algorithms able to cope with undersampled data. It introduces the concept of compressive sampling, which is also called compressed sensing.
Описание: This book serves as a hands-on guide to RF tunable devices, circuits and subsystems. An innovative of modeling for tunable devices and networks is described, along with a new tuning algorithm, adaptive matching network control approach, and novel filter frequency automatic control loop.
Автор: Omar Oreifej; Mubarak Shah Название: Robust Subspace Estimation Using Low-Rank Optimization ISBN: 3319352482 ISBN-13(EAN): 9783319352480 Издательство: Springer Рейтинг: Цена: 13275.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: By minimizing the rank of the matrix containing observations drawn from images, the authors demonstrate how to solve four fundamental computer vision problems, including video denosing, background subtraction, motion estimation, and activity recognition.
Автор: Saad Ali; Ko Nishino; Dinesh Manocha; Mubarak Shah Название: Modeling, Simulation and Visual Analysis of Crowds ISBN: 1461484820 ISBN-13(EAN): 9781461484820 Издательство: Springer Рейтинг: Цена: 15372.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The goal of this book is to provide the readers a comprehensive map towards the common goal of better analyzing and synthesizing the pedestrian movement in dense, heterogeneous crowds.
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